Data France

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Nombre de décès COVID-19 journaliers en France

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Hospitalisations quotidiennes pour COVID-19 en Ile de France eten France

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Patients hospitalisés pour COVID-19 en Ile de France eten France

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Hospitalisations quotidiennes en réanimation pour COVID-19en Ile de France et en France

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Patients hospitalisés en réanimation pour COVID-19en Ile de France et en France

Data monde

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Nombre de décès COVID-19 cumulés depuis le 1er mars 2020

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Nombre de décès COVID-19 journaliers en Italie

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Nombre de décès COVID-19 journaliers en Angleterre

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Nombre de décès COVID-19 journaliers au USA

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Nombre de décès COVID-19 journaliers en Allemagne

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Nombre de décès COVID-19 journaliers aux Pays-Bas

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Nombre de décès COVID-19 journaliers au Brésil

Surmortalité

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Mortalité journalière toutes causes confondues en France

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Mortalité cumulée toutes causes confondues en France

Sources : 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE & Données hospitalières relatives à l’épidémie de COVID-19 par Santé publique France & Fichier des personnes décédées, Institut National de la Statistique et des Etudes Economiques (Insee)

---
title: "COVID-19 
" author: "AGC" date: '`r format(Sys.time(), "%d %B %Y, %H:%M")`' output: flexdashboard::flex_dashboard: vertical_layout: scroll orientation: rows social: menu source_code: embed runtime: shiny --- ```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE) ``` ```{r, include=FALSE} library(directlabels) library(lubridate) library(tidyverse) library(ggpmisc) library(ggrepel) library(plotly) library(plyr) library(flexdashboard) setwd("/Users/antoinegaudetchardonnet/Git/COVID-19/COVID-19/Data") baseDCj <- read.csv ("DCjours_annuelV2.csv") baseDCj$Date <- as.Date (baseDCj$Date) baseDCj$Deces <- as.numeric (baseDCj$Deces) baseDCj$Annee <- as.factor (baseDCj$Annee) baseDCj <- baseDCj[,-1] baseDCj$cumsum <- do.call(c, tapply(baseDCj$Deces, baseDCj$Annee, FUN=cumsum)) csv <- paste("ptime_series_19-covid-Deaths_",Sys.Date(),".csv", sep="" ) csv2 <- paste("ptime_series_19-covid-Hospit",Sys.Date(),".csv", sep="" ) download.file("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv", destfile = csv, method = "curl") download.file("https://www.data.gouv.fr/fr/datasets/r/63352e38-d353-4b54-bfd1-f1b3ee1cabd7", destfile = csv2, method = "curl") setwd("/Users/antoinegaudetchardonnet/Git/COVID-19/COVID-19/") # Base Johns Hopkins CSSE base <- read.csv("https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv") # Suppression de la colonne des Provinces base <- base[base$"Province.State" == "",] #Creation des data frame à 3 colonnes : nombres DC, date, Pays # baseGermany <- base %>% filter (Country.Region == "Germany") baseGermany <- baseGermany[,c(-1:-43)] baseGermany <- as.numeric(baseGermany) baseItaly <- base %>% filter (Country.Region == "Italy") baseItaly <- baseItaly[,c(-1:-43)] baseItaly <- as.numeric(baseItaly) baseFrance <- base %>% filter (Country.Region == "France") baseFrance <- baseFrance[,c(-1:-43)] x <- ncol (baseFrance) baseFrance <- as.numeric(baseFrance) baseIran <- base %>% filter (Country.Region == "Iran") baseIran <- baseIran[,c(-1:-43)] baseIran <- as.numeric(baseIran) baseUS <- base %>% filter (Country.Region == "US") baseUS <- baseUS[,c(-1:-43)] baseUS <- as.numeric(baseUS) baseUK <- base %>% filter (Country.Region == "United Kingdom") baseUK <- baseUK[,c(-1:-43)] baseUK <- as.numeric(baseUK) basee <- base %>% filter (Country.Region == "Spain") basee <- basee[,c(-1:-43)] basee <- as.numeric(basee) basen <- base %>% filter (Country.Region == "Netherlands") basen <- basen[,c(-1:-43)] basen <- as.numeric(basen) baseb <- base %>% filter (Country.Region == "Brazil") baseb <- baseb[,c(-1:-43)] baseb <- as.numeric(baseb) # creation du Data frame avec la date du 01/03 au jours dernier jour de la abse initiale df <- data.frame(baseFrance,(as.Date("2020-03-01") + 0:(x-1)),"France", c(1:x)) di <- data.frame(baseItaly,(as.Date("2020-03-01") + 0:(x-1)),"Italie", c(1:x)) dg <- data.frame(baseGermany,(as.Date("2020-03-01") + 0:(x-1)),"Allemagne", c(1:x)) dus <- data.frame(baseUS,(as.Date("2020-03-01") + 0:(x-1)),"US", c(1:x)) duk <- data.frame(baseUK,(as.Date("2020-03-01") + 0:(x-1)),"UK", c(1:x)) dir <- data.frame(baseIran,(as.Date("2020-03-01") + 0:(x-1)),"Iran", c(1:x)) de <- data.frame(basee,(as.Date("2020-03-01") + 0:(x-1)),"Espagne", c(1:x)) dn<- data.frame(basen,(as.Date("2020-03-01") + 0:(x-1)),"Pays-Bas", c(1:x)) db <- data.frame(baseb,(as.Date("2020-03-01") + 0:(x-1)),"Bresil", c(1:x)) colnames(df) <- c("dc","Date","Pays","jour") colnames(di) <- c("dc","Date","Pays","jour") colnames(dg) <- c("dc","Date","Pays","jour") colnames(dus) <- c("dc","Date","Pays","jour") colnames(duk) <- c("dc","Date","Pays","jour") colnames(dir) <- c("dc","Date","Pays","jour") colnames(de) <- c("dc","Date","Pays","jour") colnames(dn) <- c("dc","Date","Pays","jour") colnames(db) <- c("dc","Date","Pays","jour") # base des décès journaliers par pays (différence entre le nombre de totale pour chaque journée dfj <- data.frame(dc = c(0,diff(df$dc)), Date = c(df$Date), Pays = "Journaliers", jour = c(1:x)) dij <- data.frame(dc = c(0,diff(di$dc)), Date = c(di$Date), Pays = "Journaliers", jour = c(1:x)) dukj <- data.frame(dc = c(0,diff(duk$dc)), Date = c(duk$Date), Pays = "yJournaliers", jour = c(1:x)) dusj <- data.frame(dc = c(0,diff(dus$dc)), Date = c(dus$Date), Pays = "yJournaliers", jour = c(1:x)) dgj <- data.frame(dc = c(0,diff(dg$dc)), Date = c(dg$Date), Pays = "Journaliers", jour = c(1:x)) dnj <- data.frame(dc = c(0,diff(dn$dc)), Date = c(dn$Date), Pays = "yJournaliers", jour = c(1:x)) dbj <- data.frame(dc = c(0,diff(db$dc)), Date = c(db$Date), Pays = "Journaliers", jour = c(1:x)) baseIFG <- rbind(di,df,dg, dus, duk,dir,de,dn, db) # Base Santé publique france hospit <- read.csv2("https://www.data.gouv.fr/fr/datasets/r/63352e38-d353-4b54-bfd1-f1b3ee1cabd7") # Suppression de la colonne sexe et mise en forme de la base hospit <- hospit[hospit$sexe == "0",] transform(hospit, dep = as.numeric(dep)) transform(hospit, jour = as.Date(jour)) hospit$jour <- as.Date(hospit$jour) hospitidf <- hospit[hospit$dep == 75 | hospit$dep == 91 |hospit$dep == 92 |hospit$dep == 93 |hospit$dep == 94 |hospit$dep == 95 |hospit$dep == 77 ,] # hosp = hospitalisation en France hosp <- data.frame(aggregate(hospit$hosp, by = list(typ2 = hospit$jour), sum),"France") hospidf <- data.frame(aggregate(hospitidf$hosp, by = list(typ2 = hospitidf$jour), sum), "IdF") colnames(hosp) <- c("Date","hosp","lieu") colnames(hospidf) <- c("Date","hosp","lieu") # data hospitalisation en réa rea <- data.frame(aggregate(hospit$rea, by = list(typ2 = hospit$jour), sum),"France") reaidf <- data.frame(aggregate(hospitidf$rea, by = list(typ2 = hospitidf$jour), sum), "IdF") colnames(rea) <- c("Date","rea","lieu") colnames(reaidf) <- c("Date","rea","lieu") # Base Santé publique hospit quotidienne france incid_hospit <- read.csv2("https://www.data.gouv.fr/en/datasets/r/6fadff46-9efd-4c53-942a-54aca783c30c") # Mise en forme de la base incid_hospit$dep[incid_hospit$dep %in% c("2A", "2B")] <- "20" transform(incid_hospit, dep = as.numeric(dep)) transform(incid_hospit, jour = as.Date(jour)) incid_hospit$jour <- as.Date(incid_hospit$jour) incid_hospitidf <- incid_hospit[incid_hospit$dep == 75 | incid_hospit$dep == 91 |incid_hospit$dep == 92 |incid_hospit$dep == 93 |incid_hospit$dep == 94 |incid_hospit$dep == 95 |incid_hospit$dep == 77 ,] # hosp = hospitalisation quotdienne en France incid_hosp <- data.frame(aggregate(incid_hospit$incid_hosp, by = list(typ2 = incid_hospit$jour), sum),"France") incid_hospidf <- data.frame(aggregate(incid_hospitidf$incid_hosp, by = list(typ2 = incid_hospitidf$jour), sum), "IdF") colnames(incid_hosp) <- c("Date","hosp","lieu") colnames(incid_hospidf) <- c("Date","hosp","lieu") # data hospitalisation quotdienne en réa incid_rea <- data.frame(aggregate(incid_hospit$incid_rea, by = list(typ2 = incid_hospit$jour), sum),"France") incid_reaidf <- data.frame(aggregate(incid_hospitidf$incid_rea, by = list(typ2 = incid_hospitidf$jour), sum), "IdF") colnames(incid_rea) <- c("Date","rea","lieu") colnames(incid_reaidf) <- c("Date","rea","lieu") #Liste des bouton plotly à masquer listmodbar <- c("zoom2d", "pan2d", "select2d", "lasso2d", "zoomIn2d", "zoomOut2d", "autoScale2d", "resetScale2d", "hoverClosestCartesian", "hoverCompareCartesian", "zoom3d", "pan3d", "resetCameraDefault3d", "resetCameraLastSave3d", "hoverClosest3d", "orbitRotation", "tableRotation", "zoomInGeo", "zoomOutGeo", "resetGeo", "hoverClosestGeo", "sendDataToCloud", "hoverClosestGl2d", "hoverClosestPie", "toggleHover", "resetViews", "toggleSpikelines", "resetViewMapbox") ``` Data France ======================================================================= Row ----------------------------------------------------------------------- ### Nombre de décès COVID-19 journaliers en France ```{r , echo=FALSE, warning=FALSE, message=FALSE } # dc/ jours en France # initialement geom-col décès par jour et total de mort puis nombre total non affiché par soucis d'echelle p<- ggplot(dfj, aes(Date, dc, label=dc, text = paste0("Nombre de décès : ", dc)), frame = Date) + #ggtitle("Nombre de décès COVID-19 journaliers en France") + geom_col(fill = "#4DB4C1") + scale_y_continuous(name="Nombre de décès COVID-19 journaliers", limits=c(0, 1500)) + theme_classic() + theme(plot.title = element_text( size=10, face="bold", color = "#317eac")) + theme (axis.text.y = element_text(size=8)) + theme (axis.title.y = element_text(size=8)) +theme (axis.text.x = element_text(size=8)) + theme (axis.title.x = element_text(size=8)) + theme(legend.position='none') fig <- ggplotly(p, tooltip = c("Date", "text")) %>% config(modeBarButtonsToRemove = listmodbar, displaylogo = FALSE, toImageButtonOptions = list(format = "png", width = 800, height = 600)) fig ``` Row ----------------------------------------------------------------------- ### Hospitalisations quotidiennes pour COVID-19 en Ile de France et\n en France ```{r , echo=FALSE, warning=FALSE, message=FALSE } # hospit COVID # hospit quotidiennes p<- ggplot(NULL, aes(Date, hosp, text = paste0("Nombre d'hospitalisations : ", hosp))) + geom_col(data = incid_hosp, alpha = 0.3, fill = "#FDAC88") + geom_col(data = incid_hospidf, alpha = 1, fill = "#4DB4C1") + #ggtitle("Hospitalisations quotidiennes pour COVID-19 en Ile de France et\n en France") + scale_y_continuous(name="Nombre de patients hospitalisés") + theme_classic() + theme(plot.title = element_text( size=10, face="bold", color = "#317eac")) + theme (axis.text.y = element_text(size=8)) + theme (axis.title.y = element_text(size=8)) +theme (axis.text.x = element_text(size=8)) + theme (axis.title.x = element_text(size=8)) + theme(legend.position='none') fig <- ggplotly(p, tooltip = c("Date", "text")) %>% config(modeBarButtonsToRemove = listmodbar, displaylogo = FALSE, toImageButtonOptions = list(format = "png", width = 800, height = 600)) fig ``` Row ----------------------------------------------------------------------- ### Patients hospitalisés pour COVID-19 en Ile de France et\n en France ```{r , echo=FALSE, warning=FALSE, message=FALSE } # hospit en cours p<- ggplot(NULL, aes(x = Date, y = hosp, label = hosp, text = paste0("Nombre d'hospitalisations : ", hosp))) + geom_col(data = hosp, alpha = 0.3, fill = "#FDAC88") + geom_col(data = hospidf, alpha = 1, fill = "#4DB4C1") + #ggtitle("Patients hospitalisés pour COVID-19 en Ile de France et\n en France") + scale_y_continuous(name="Nombre de patients hospitalisés") + theme_classic() + theme(plot.title = element_text( size=10, face="bold", color = "#317eac")) + theme (axis.text.y = element_text(size=8)) + theme (axis.title.y = element_text(size=8)) +theme (axis.text.x = element_text(size=8)) + theme (axis.title.x = element_text(size=8)) + theme(legend.position='none') fig <- ggplotly(p, tooltip = c("Date", "text")) %>% config(modeBarButtonsToRemove = listmodbar, displaylogo = FALSE, toImageButtonOptions = list(format = "png", width = 800, height = 600)) fig ``` Row ----------------------------------------------------------------------- ### Hospitalisations quotidiennes en réanimation pour COVID-19\n en Ile de France et en France ```{r , echo=FALSE, warning=FALSE, message=FALSE } # hospit quotidnne en réa p<- ggplot(NULL, aes(Date, rea, text = paste0("Nombre d'hospitalisations : ", rea))) + geom_col(data = incid_rea, alpha = 0.3, fill = "#FDAC88") + geom_col(data = incid_reaidf, alpha = 1, fill = "#4DB4C1") + #ggtitle("Hospitalisations quotidiennes en réanimation pour COVID-19\n en Ile de France et en France") + scale_y_continuous(name="Nombre de patients hospitalisés") + theme_classic() + theme(plot.title = element_text( size=10, face="bold", color = "#317eac")) + theme (axis.text.y = element_text(size=8)) + theme (axis.title.y = element_text(size=8)) +theme (axis.text.x = element_text(size=8)) + theme (axis.title.x = element_text(size=8)) + theme(legend.position='none') fig <- ggplotly(p, tooltip = c("Date", "text")) %>% config(modeBarButtonsToRemove = listmodbar, displaylogo = FALSE, toImageButtonOptions = list(format = "png", width = 800, height = 600)) fig ``` Row ----------------------------------------------------------------------- ### Patients hospitalisés en réanimation pour COVID-19\n en Ile de France et en France ```{r , echo=FALSE, warning=FALSE, message=FALSE } # Patient en réa p<- ggplot(NULL, aes(Date, rea, text = paste0("Nombre d'hospitalisations : ", rea))) + geom_col(data = rea, alpha = 0.3, fill = "#FDAC88") + geom_col(data = reaidf, alpha = 1, fill = "#4DB4C1") + #ggtitle("Patients hospitalisés en réanimation pour COVID-19\n en Ile de France et en France") + scale_y_continuous(name="Nombre de patients hospitalisés") + theme_classic() + theme(plot.title = element_text( size=10, face="bold", color = "#317eac")) + theme (axis.text.y = element_text(size=8)) + theme (axis.title.y = element_text(size=8)) +theme (axis.text.x = element_text(size=8)) + theme (axis.title.x = element_text(size=8)) + theme(legend.position='none') fig <- ggplotly(p, tooltip = c("Date", "text")) %>% config(modeBarButtonsToRemove = listmodbar, displaylogo = FALSE, toImageButtonOptions = list(format = "png", width = 800, height = 600)) fig ``` Data monde ======================================================================= Row ----------------------------------------------------------------------- ### Nombre de décès COVID-19 cumulés depuis le 1er mars 2020 ```{r, echo=FALSE, warning=FALSE, message=FALSE} # warning et message false pour ne pas affiché les alertes # Courbe des décès cumulés # scale_x_date : limits du 01/03 au j+2 permet l'affichage de directlab # scale_y_continuous : affiche la dernière valeur de chaque courbe p <- ggplot (baseIFG, aes(x=Date, y=dc, fill=Pays, colour=Pays, text = dc)) + #ggtitle("Nombre de décès COVID-19 cumulés depuis le 1er mars 2020") + geom_line() + scale_x_date(date_breaks = "month", date_labels = "%d %B", limits = c(as.Date("2020-03-01"),as.Date((Sys.Date())))) + scale_y_continuous(name="Nombre de décès COVID cumulés") + theme_classic() + theme(plot.title = element_text(size=10, face="bold", color = "#317eac")) fig <- ggplotly(p, tooltip = c("colour", "Date", "text")) %>% config(modeBarButtonsToRemove = listmodbar, displaylogo = FALSE, toImageButtonOptions = list(format = "png", width = 800, height = 600)) %>% layout(showlegend = FALSE) fig ``` Row ----------------------------------------------------------------------- ### Nombre de décès COVID-19 journaliers en Italie ```{r , echo=FALSE, warning=FALSE, message=FALSE } # dc/ jours en Italie p<- ggplot(dij, aes(Date, dc, label=dc, text = paste0("Nombre de décès : ", dc))) + #ggtitle("Nombre de décès COVID-19 journaliers en Italie") + geom_col(fill = "#4DB4C1") + scale_y_continuous(name="Nombre de décès COVID-19 journaliers", limits=c(0, 1500)) + theme_classic() + theme(plot.title = element_text( size=10, face="bold", color = "#317eac")) + theme (axis.text.y = element_text(size=8)) + theme (axis.title.y = element_text(size=8)) +theme (axis.text.x = element_text(size=8)) + theme (axis.title.x = element_text(size=8)) + theme(legend.position='none') fig <- ggplotly(p, tooltip = c("Date", "text")) %>% config(modeBarButtonsToRemove = listmodbar, displaylogo = FALSE, toImageButtonOptions = list(format = "png", width = 800, height = 600)) fig ``` Row ----------------------------------------------------------------------- ### Nombre de décès COVID-19 journaliers en Angleterre ```{r , echo=FALSE, warning=FALSE, message=FALSE } # dc/ jours en UK p<- ggplot(dukj, aes(Date, dc, label=dc, text = paste0("Nombre de décès : ", dc))) + #ggtitle("Nombre de décès COVID-19 journaliers en Angleterre") + geom_col(fill = "#4DB4C1") + scale_y_continuous(name="Nombre de décès COVID-19 journaliers", limits=c(0, 1500)) + theme_classic() + theme(plot.title = element_text( size=10, face="bold", color = "#317eac")) + theme (axis.text.y = element_text(size=8)) + theme (axis.title.y = element_text(size=8)) +theme (axis.text.x = element_text(size=8)) + theme (axis.title.x = element_text(size=8)) + theme(legend.position='none') fig <- ggplotly(p, tooltip = c("Date", "text")) %>% config(modeBarButtonsToRemove = listmodbar, displaylogo = FALSE, toImageButtonOptions = list(format = "png", width = 800, height = 600)) fig ``` Row ----------------------------------------------------------------------- ### Nombre de décès COVID-19 journaliers au USA ```{r , echo=FALSE, warning=FALSE, message=FALSE} # dc/ jours en US p<- ggplot(dusj, aes(Date, dc, label=dc, text = paste0("Nombre de décès : ", dc))) + #ggtitle("Nombre de décès COVID-19 journaliers au USA") + geom_col(fill = "#4DB4C1") + scale_y_continuous(name="Nombre de décès COVID-19 journaliers", limits=c(0, 4000)) + theme_classic() + theme(plot.title = element_text( size=10, face="bold", color = "#317eac")) + theme (axis.text.y = element_text(size=8)) + theme (axis.title.y = element_text(size=8)) +theme (axis.text.x = element_text(size=8)) + theme (axis.title.x = element_text(size=8)) + theme(legend.position='none') fig <- ggplotly(p, tooltip = c("Date", "text")) %>% config(modeBarButtonsToRemove = listmodbar, displaylogo = FALSE, toImageButtonOptions = list(format = "png", width = 800, height = 600)) fig ``` Row ----------------------------------------------------------------------- ### Nombre de décès COVID-19 journaliers en Allemagne ```{r , echo=FALSE, warning=FALSE, message=FALSE } # dc/ jours en Allemagne p<- ggplot(dgj, aes(Date, dc, label=dc, text = paste0("Nombre de décès : ", dc))) + #ggtitle("Nombre de décès COVID-19 journaliers en Allemagne") + geom_col(fill = "#4DB4C1") + scale_y_continuous(name="Nombre de décès COVID-19 journaliers", limits=c(0, 1500)) + theme_classic() + theme(plot.title = element_text( size=10, face="bold", color = "#317eac")) + theme (axis.text.y = element_text(size=8)) + theme (axis.title.y = element_text(size=8)) +theme (axis.text.x = element_text(size=8)) + theme (axis.title.x = element_text(size=8)) + theme(legend.position='none') fig <- ggplotly(p, tooltip = c("Date", "text")) %>% config(modeBarButtonsToRemove = listmodbar, displaylogo = FALSE, toImageButtonOptions = list(format = "png", width = 800, height = 600)) fig ``` Row ----------------------------------------------------------------------- ### Nombre de décès COVID-19 journaliers aux Pays-Bas ```{r , echo=FALSE, warning=FALSE, message=FALSE } # dc/ jours aux pays-bas p<- ggplot(dnj, aes(Date, dc, label=dc, text = paste0("Nombre de décès : ", dc))) + #ggtitle("Nombre de décès COVID-19 journaliers aux Pays-Bas") + geom_col(fill = "#4DB4C1") + scale_y_continuous(name="Nombre de décès COVID-19 journaliers", limits=c(0, 1500)) + theme_classic() + theme(plot.title = element_text( size=10, face="bold", color = "#317eac")) + theme (axis.text.y = element_text(size=8)) + theme (axis.title.y = element_text(size=8)) +theme (axis.text.x = element_text(size=8)) + theme (axis.title.x = element_text(size=8)) + theme(legend.position='none') fig <- ggplotly(p, tooltip = c("Date", "text")) %>% config(modeBarButtonsToRemove = listmodbar, displaylogo = FALSE, toImageButtonOptions = list(format = "png", width = 800, height = 600)) fig ``` Row ----------------------------------------------------------------------- ### Nombre de décès COVID-19 journaliers au Brésil ```{r , echo=FALSE, warning=FALSE, message=FALSE } # dc/ jours aux Brésil p<- ggplot(dbj, aes(Date, dc, label=dc, text = paste0("Nombre de décès : ", dc))) + #ggtitle("Nombre de décès COVID-19 journaliers au Brésil") + geom_col(fill = "#4DB4C1") + scale_y_continuous(name="Nombre de décès COVID-19 journaliers", limits=c(0, 3500)) + theme_classic() + theme(plot.title = element_text( size=10, face="bold", color = "#317eac")) + theme (axis.text.y = element_text(size=8)) + theme (axis.title.y = element_text(size=8)) +theme (axis.text.x = element_text(size=8)) + theme (axis.title.x = element_text(size=8)) + theme(legend.position='none') fig <- ggplotly(p, tooltip = c("Date", "text")) %>% config(modeBarButtonsToRemove = listmodbar, displaylogo = FALSE, toImageButtonOptions = list(format = "png", width = 800, height = 600)) fig ``` Surmortalité ======================================================================= Row ----------------------------------------------------------------------- ### Mortalité journalière toutes causes confondues en France ```{r , echo=FALSE, warning=FALSE, message=FALSE} # DC par jours DCj <- ggplot (baseDCj, aes(x=Date, y=Deces, color=Annee, label = Deces)) + #ggtitle("Mortalité journalière toutes causes confondues en France") + geom_line () + theme_classic() + theme(plot.title = element_text( size=10, face="bold", color = "#317eac")) + theme (axis.text.y = element_text(size=8)) + theme (axis.title.y = element_text(size=8)) +theme (axis.text.x = element_text(size=8)) + theme (axis.title.x = element_text(size=8)) + scale_x_date(date_breaks = "month", date_labels = "%b", limits = c(as.Date("2020-01-01"),as.Date("2021-01-10"))) + scale_y_continuous(name="Nombre de décès journaliers") fig <- ggplotly(DCj, tooltip = c("Annee", "label")) %>% config(modeBarButtonsToRemove = listmodbar, displaylogo = FALSE, toImageButtonOptions = list(format = "png", width = 800, height = 600)) %>% layout(showlegend = FALSE) fig ``` Row ----------------------------------------------------------------------- ### Mortalité cumulée toutes causes confondues en France ```{r , echo=FALSE, warning=FALSE, message=FALSE} # DC cumulé DCcum <- ggplot (baseDCj, aes(x=Date, y=cumsum, color=Annee, text = cumsum)) + #ggtitle("Mortalité cumulée toutes causes confondues en France") + geom_line () + theme_classic() + theme(plot.title = element_text( size=10, face="bold", color = "#317eac")) + theme (axis.text.y = element_text(size=8)) + theme (axis.title.y = element_text(size=8)) +theme (axis.text.x = element_text(size=8)) + theme (axis.title.x = element_text(size=8)) + scale_x_date(date_breaks = "month", date_labels = "%b", limits = c(as.Date("2020-01-01"),as.Date("2021-01-10"))) + scale_y_continuous(name="Nombre de décès cumulés", , limits=c(0, 700000)) fig <- ggplotly(DCcum, tooltip = c("Annee", "text")) %>% config(modeBarButtonsToRemove = listmodbar, displaylogo = FALSE, toImageButtonOptions = list(format = "png", width = 800, height = 600, filename = 'Perinat_Data')) %>% layout(showlegend = FALSE) # fig <- ggplotly(DCcum) %>% config(displayModeBar=FALSE) %>% layout(xaxis=list(fixedrange=TRUE)) %>% layout(yaxis=list(fixedrange=TRUE)) fig # direct.label(DCcum, method="last.bumpup") ``` Sources : 2019 Novel Coronavirus COVID-19 (2019-nCoV) Data Repository by Johns Hopkins CSSE & Données hospitalières relatives à l'épidémie de COVID-19 par Santé publique France & Fichier des personnes décédées, Institut National de la Statistique et des Etudes Economiques (Insee)